if(!require("remotes")) install.packages("remotes")
if(!require("MultiEWCE")) remotes::install_github("neurogenomics/MutltiEWCE")results <- MultiEWCE::load_example_results()
ctd <- MultiEWCE::load_example_ctd()top_targets <- MultiEWCE::prioritise_targets(results = results,
ctd = ctd,
top_n = 3)## Prioritising gene targets.## Importing existing file: /Users/schilder/Library/Caches/org.R-project.R/R/HPOExplorer/data/phenotype_to_genes.txt## Prioritised targets:
## - 424,039 results
## - 5,507 phenotypes
## - 77 cell types
## - 0 associated diseases
## - 0 genes## Filtering @ q-value <= 0.05## Prioritised targets:
## - 7,545 results
## - 2,527 phenotypes
## - 77 cell types
## - 0 associated diseases
## - 0 genes## Filtering @ fold-change >= 1## Prioritised targets:
## - 7,545 results
## - 2,527 phenotypes
## - 77 cell types
## - 0 associated diseases
## - 0 genes## Annotating phenos with Tiers.## Prioritised targets:
## - 106 results
## - 11 phenotypes
## - 36 cell types
## - 0 associated diseases
## - 0 genes## Importing existing file: /Users/schilder/Library/Caches/org.R-project.R/R/HPOExplorer/data/phenotype.hpoa## Annotating phenos with Onset.## Importing existing file: /Users/schilder/Library/Caches/org.R-project.R/R/HPOExplorer/data/phenotype.hpoa## Prioritised targets:
## - 523 results
## - 11 phenotypes
## - 36 cell types
## - 42 associated diseases
## - 0 genes## 20 / 36 of cell types kept.## Prioritised targets:
## - 342 results
## - 11 phenotypes
## - 20 cell types
## - 42 associated diseases
## - 0 genes## Filtering by gene size.## Converting phenos to GRanges.## Loading required namespace: ensembldb## Gathering gene metadata## Loading required namespace: EnsDb.Hsapiens.v75## 120 / 2,213 genes kept.## Filtering by specificity_quantile.## Filtering by mean_exp_quantile.## Prioritised targets:
## - 224 results
## - 9 phenotypes
## - 0 cell types
## - 0 associated diseases
## - 70 genes## Prioritised targets:
## - 335 results
## - 9 phenotypes
## - 15 cell types
## - 39 associated diseases
## - 24 genes## Sorting rows.## Finding top 3 gene targets per: HPO_ID, CellType## Prioritised targets:
## - 80 results
## - 9 phenotypes
## - 15 cell types
## - 17 associated diseases
## - 21 genesall_targets <- MultiEWCE::prioritise_targets(results = results,
ctd = ctd,
top_n = NULL)## Prioritising gene targets.## Importing existing file: /Users/schilder/Library/Caches/org.R-project.R/R/HPOExplorer/data/phenotype_to_genes.txt## Prioritised targets:
## - 424,039 results
## - 5,507 phenotypes
## - 77 cell types
## - 0 associated diseases
## - 0 genes## Filtering @ q-value <= 0.05## Prioritised targets:
## - 7,545 results
## - 2,527 phenotypes
## - 77 cell types
## - 0 associated diseases
## - 0 genes## Filtering @ fold-change >= 1## Prioritised targets:
## - 7,545 results
## - 2,527 phenotypes
## - 77 cell types
## - 0 associated diseases
## - 0 genes## Annotating phenos with Tiers.## Prioritised targets:
## - 106 results
## - 11 phenotypes
## - 36 cell types
## - 0 associated diseases
## - 0 genes## Importing existing file: /Users/schilder/Library/Caches/org.R-project.R/R/HPOExplorer/data/phenotype.hpoa## Annotating phenos with Onset.## Importing existing file: /Users/schilder/Library/Caches/org.R-project.R/R/HPOExplorer/data/phenotype.hpoa## Prioritised targets:
## - 523 results
## - 11 phenotypes
## - 36 cell types
## - 42 associated diseases
## - 0 genes## 20 / 36 of cell types kept.## Prioritised targets:
## - 342 results
## - 11 phenotypes
## - 20 cell types
## - 42 associated diseases
## - 0 genes## Filtering by gene size.## Converting phenos to GRanges.## Gathering gene metadata## 120 / 2,213 genes kept.## Filtering by specificity_quantile.## Filtering by mean_exp_quantile.## Prioritised targets:
## - 224 results
## - 9 phenotypes
## - 0 cell types
## - 0 associated diseases
## - 70 genes## Prioritised targets:
## - 335 results
## - 9 phenotypes
## - 15 cell types
## - 39 associated diseases
## - 24 genes## Sorting rows.## Prioritised targets:
## - 335 results
## - 9 phenotypes
## - 15 cell types
## - 39 associated diseases
## - 24 genesdf_agg <- MultiEWCE::agg_results(phenos = all_targets,
count_var = "CellType",
group_var = "Phenotype")## Aggregating results by group_var='Phenotype'## Adding HPO IDs.## Importing existing file: /Users/schilder/Library/Caches/org.R-project.R/R/HPOExplorer/data/phenotype_to_genes.txtMultiEWCE::create_dt(df_agg)## Loading required namespace: DTSubset phenotypes to those included in intellectual disability, and are related to cognition.
df_intel <- all_targets[disease_characteristic=="Intellectual disability" &
(!Phenotype %in% c("Choreoathetosis","Coma")),]top_genes <- sort(table(df_intel$Gene),
decreasing = TRUE)
print(top_genes)##
## SOX3 SIX6 POU3F4 GSX2 SOX2 FOXG1 PIGY
## 42 41 29 28 28 27 23
## TUBB2A PROP1 GPR88 RTL1 SNORD116-1 SNORD118 FOXH1
## 19 18 14 14 14 14 1
## HOXA2 PRRT2 SLC18A3
## 1 1 1top_celltypes <- sort(table(unique(df_intel[,c("Phenotype","HPO_ID","CellType")])$CellType),
decreasing = TRUE)
print(top_celltypes)##
## Excitatory neurons Ganglion cells Granule neurons Inhibitory neurons
## 4 4 3 3
## Purkinje neurons Amacrine cells Astrocytes ENS glia
## 3 2 2 2
## Horizontal cells Oligodendrocytes Bipolar cells Visceral neurons
## 2 2 1 1Generate a network from the top phenotype-celltype-gene associations.
vn <- MultiEWCE::prioritise_targets_network(top_targets = top_targets,
show_plot = FALSE)## Loading required namespace: igraph## Loading required namespace: visNetwork## Creating network.## Creating plot.## Saving plot ==> /var/folders/zq/h7mtybc533b1qzkys_ttgpth0000gn/T//RtmpS1cSQt/file11e11564e05eb_prioritise_targets_network.htmlvisNetwork::renderVisNetwork(vn$plot)utils::sessionInfo()## R version 4.2.1 (2022-06-23)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Big Sur ... 10.16
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] MultiEWCE_0.1.3 remotes_2.4.2
##
## loaded via a namespace (and not attached):
## [1] utf8_1.2.2 R.utils_2.12.2
## [3] tidyselect_1.2.0 RSQLite_2.2.20
## [5] AnnotationDbi_1.60.0 htmlwidgets_1.6.1
## [7] grid_4.2.1 BiocParallel_1.32.5
## [9] munsell_0.5.0 codetools_0.2-18
## [11] DT_0.27 colorspace_2.1-0
## [13] Biobase_2.58.0 filelock_1.0.2
## [15] knitr_1.42 rstudioapi_0.14
## [17] orthogene_1.4.1 stats4_4.2.1
## [19] SingleCellExperiment_1.20.0 ggsignif_0.6.4
## [21] MatrixGenerics_1.10.0 GenomeInfoDbData_1.2.9
## [23] bit64_4.0.5 coda_0.19-4
## [25] vctrs_0.5.2 treeio_1.22.0
## [27] generics_0.1.3 xfun_0.36
## [29] BiocFileCache_2.6.0 R6_2.5.1
## [31] GenomeInfoDb_1.34.6 pals_1.7
## [33] AnnotationFilter_1.22.0 bitops_1.0-7
## [35] cachem_1.0.6 gridGraphics_0.5-1
## [37] DelayedArray_0.24.0 assertthat_0.2.1
## [39] promises_1.2.0.1 BiocIO_1.8.0
## [41] scales_1.2.1 gtable_0.3.1
## [43] ontologyPlot_1.6 ensembldb_2.22.0
## [45] rlang_1.0.6 rtracklayer_1.58.0
## [47] rstatix_0.7.1 lazyeval_0.2.2
## [49] dichromat_2.0-0.1 broom_1.0.3
## [51] BiocManager_1.30.19 yaml_2.3.7
## [53] reshape2_1.4.4 HPOExplorer_0.99.2
## [55] abind_1.4-5 GenomicFeatures_1.50.4
## [57] ggnetwork_0.5.10 crosstalk_1.2.0
## [59] backports_1.4.1 httpuv_1.6.8
## [61] tools_4.2.1 ggplotify_0.1.0
## [63] statnet.common_4.8.0 ggplot2_3.4.0
## [65] ellipsis_0.3.2 jquerylib_0.1.4
## [67] paintmap_1.0 BiocGenerics_0.44.0
## [69] Rcpp_1.0.10 plyr_1.8.8
## [71] visNetwork_2.1.2 progress_1.2.2
## [73] zlibbioc_1.44.0 purrr_1.0.1
## [75] RCurl_1.98-1.9 prettyunits_1.1.1
## [77] ggpubr_0.5.0 S4Vectors_0.36.1
## [79] SummarizedExperiment_1.28.0 grr_0.9.5
## [81] magrittr_2.0.3 data.table_1.14.6
## [83] ProtGenerics_1.30.0 matrixStats_0.63.0
## [85] hms_1.1.2 patchwork_1.1.2
## [87] mime_0.12 evaluate_0.20
## [89] xtable_1.8-4 XML_3.99-0.13
## [91] EWCE_1.6.0 IRanges_2.32.0
## [93] compiler_4.2.1 biomaRt_2.54.0
## [95] tibble_3.1.8 maps_3.4.1
## [97] crayon_1.5.2 R.oo_1.25.0
## [99] htmltools_0.5.4 ggfun_0.0.9
## [101] later_1.3.0 tidyr_1.3.0
## [103] aplot_0.1.9 DBI_1.1.3
## [105] ExperimentHub_2.6.0 gprofiler2_0.2.1
## [107] dbplyr_2.3.0 rappdirs_0.3.3
## [109] babelgene_22.9 EnsDb.Hsapiens.v75_2.99.0
## [111] Matrix_1.5-3 car_3.1-1
## [113] piggyback_0.1.4 cli_3.6.0
## [115] R.methodsS3_1.8.2 parallel_4.2.1
## [117] igraph_1.3.5 GenomicRanges_1.50.2
## [119] pkgconfig_2.0.3 GenomicAlignments_1.34.0
## [121] plotly_4.10.1 xml2_1.3.3
## [123] ggtree_3.6.2 bslib_0.4.2
## [125] XVector_0.38.0 yulab.utils_0.0.6
## [127] stringr_1.5.0 digest_0.6.31
## [129] graph_1.76.0 Biostrings_2.66.0
## [131] rmarkdown_2.20 HGNChelper_0.8.1
## [133] tidytree_0.4.2 restfulr_0.0.15
## [135] curl_5.0.0 shiny_1.7.4
## [137] Rsamtools_2.14.0 rjson_0.2.21
## [139] lifecycle_1.0.3 nlme_3.1-161
## [141] jsonlite_1.8.4 carData_3.0-5
## [143] network_1.18.1 mapproj_1.2.11
## [145] viridisLite_0.4.1 limma_3.54.0
## [147] fansi_1.0.4 pillar_1.8.1
## [149] ontologyIndex_2.10 lattice_0.20-45
## [151] homologene_1.4.68.19.3.27 KEGGREST_1.38.0
## [153] fastmap_1.1.0 httr_1.4.4
## [155] interactiveDisplayBase_1.36.0 glue_1.6.2
## [157] RNOmni_1.0.1 png_0.1-8
## [159] ewceData_1.6.0 BiocVersion_3.16.0
## [161] bit_4.0.5 Rgraphviz_2.42.0
## [163] stringi_1.7.12 sass_0.4.5
## [165] blob_1.2.3 AnnotationHub_3.6.0
## [167] memoise_2.0.1 dplyr_1.0.10
## [169] ape_5.6-2